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Unoccupied aerial system enabled functional modeling of maize height reveals dynamic expression of loci.
Plant Direct ( IF 3 ) Pub Date : 2020-05-10 , DOI: 10.1002/pld3.223
Steven L Anderson 1, 2 , Seth C Murray 1 , Yuanyuan Chen 1, 3 , Lonesome Malambo 4 , Anjin Chang 5 , Sorin Popescu 4 , Dale Cope 6 , Jinha Jung 5, 7
Affiliation  

Unoccupied aerial systems (UAS) were used to phenotype growth trajectories of inbred maize populations under field conditions. Three recombinant inbred line populations were surveyed on a weekly basis collecting RGB images across two irrigation regimens (irrigated and non‐irrigated/rain fed). Plant height, estimated by the 95th percentile (P95) height from UAS generated 3D point clouds, exceeded 70% correlation (r) to manual ground truth measurements and 51% of experimental variance was explained by genetics. The Weibull sigmoidal function accurately modeled plant growth (R2: >99%; RMSE: <4 cm) from P95 genetic means. The mean asymptote was strongly correlated (r2 = 0.66–0.77) with terminal plant height. Maximum absolute growth rates (mm/day) were weakly correlated with height and flowering time. The average inflection point ranged from 57 to 60 days after sowing (DAS) and was correlated with flowering time (r2 = 0.45–0.68). Functional growth parameters (asymptote, inflection point, growth rate) alone identified 34 genetic loci, each explaining 3–15% of total genetic variation. Plant height was estimated at one‐day intervals to 85 DAS, identifying 58 unique temporal quantitative trait loci (QTL) locations. Genomic hotspots on chromosomes 1 and 3 indicated chromosomal regions associated with functional growth trajectories influencing flowering time, growth rate, and terminal growth. Temporal QTL demonstrated unique dynamic expression patterns not previously observable, and no QTL were significantly expressed throughout the entire growing season. UAS technologies improved phenotypic selection accuracy and permitted monitoring traits on a temporal scale previously infeasible using manual measurements, furthering understanding of crop development and biological trajectories.

中文翻译:

空中系统未启用的玉米高度功能建模揭示了基因座的动态表达。

在田间条件下,使用无人耕作系统(UAS)对​​近交玉米种群的生长轨迹进行表型分析。每周调查3个重组自交系种群,收集两种灌溉方案(灌溉和非灌溉/雨水灌溉)的RGB图像。用UAS生成的3D点云的第95个百分位数(P95)高度估算的植物高度,与手动地面实况测量值的相关性(r)超过70%,遗传学解释了51%的实验差异。Weibull乙状结肠功能可通过P95遗传方法准确模拟植物生长(R 2:> 99%; RMSE:<4 cm)。平均渐近线高度相关(r 2 = 0.66-0.77),终端工厂高度。最大绝对生长速率(毫米/天)与身高和开花时间弱相关。播种后的平均拐点为57到60天(DAS),并与开花时间相关(r 2 = 0.45–0.68)。仅功能性生长参数(渐近线,拐点,生长速率)就确定了34个遗传基因座,每个基因座解释了总遗传变异的3-15%。估计植物高度每隔一天间隔达到85个DAS,确定58个独特的时间定量性状基因座(QTL)位置。染色体1和3上的基因组热点表明与影响开花时间,生长速率和末端生长的功能性生长轨迹相关的染色体区域。时间性QTL表现出以前观察不到的独特动态表达模式,并且在整个生长季节中均未显着表达QTL。UAS技术提高了表型选择的准确性,并允许在以前无法使用人工测量实现的时间尺度上监控特征,
更新日期:2020-05-10
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